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#inférence LLM

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Tools & Platforms Auto-verified translation

ZML/LLMD : et si le « Docker des LLM » était français ?

SFEIR analysis (consulting-firm voice) of the launch, on July 8, 2026, of **LLMD** by the Paris-based startup **ZML** (founded by **Steeve Morin**, former VP Engineering at Zenly): an inference server that runs LLMs across **five chip families** (NVIDIA CUDA, AMD ROCm, Google TPU, Intel oneAPI, Apple Metal) **from a single codebase**. Structuring thesis: training is ceding the spotlight to **inference**, where cost per token, latency, and above all **dependence on silicon** are now decided. ZML's bet — summed up by the motto *model to metal* — is to **decouple the model from the hardware** via a compiler written in **Zig + MLIR** that produces a hermetic native binary, with no Python in the execution path, exposed through an **OpenAI-compatible API**. Two components, two licenses: **ZML** (the framework, Apache-2.0, >90% Zig) is open source; **LLMD** (the server) is not, free at launch. The article reads the object through three consulting-firm lenses — **token FinOps**, **architectural freedom** (Design to Exit), **sovereignty** (emerging European chips, integration into the VSORA Jotunn8 processor) — then delivers an unsparing verdict: it is an **alpha**, to be placed "under active watch," not to switch to today.

#LLM Inference#serving#ZML

SFEIR (voix éditoriale du cabinet)